title: A Hough transform global probabilistic approach to multiple-subject diffusion MRI tractography.
abstract: A global probabilistic fiber tracking approach based on the voting process provided by the Hough transform is introduced in this work. The proposed framework tests candidate 3D curves in the volume, assigning to each one a score computed from the diffusion images, and then selects the curves with the highest scores as the potential anatomical connections. The algorithm avoids local minima by performing an exhaustive search at the desired resolution. The technique is easily extended to multiple subjects, considering a single representative volume where the registered high-angular resolution diffusion images (HARDI) from all the subjects are non-linearly combined, thereby obtaining population-representative tracts. The tractography algorithm is run only once for the multiple subjects, and no tract alignment is necessary. We present experimental results on HARDI volumes, ranging from simulated and 1.5T physical phantoms to 7T and 4T human brain and 7T monkey brain datasets.
authors.affiliation: Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, 200 Union St. SE, MN 55455, USA. iman@umn.edu
authors.forename: Iman
authors.initials: I
authors.lastname: Aganj
authors.forename: Christophe
authors.initials: C
authors.lastname: Lenglet
authors.forename: Neda
authors.initials: N
authors.lastname: Jahanshad
authors.forename: Essa
authors.initials: E
authors.lastname: Yacoub
authors.forename: Noam
authors.initials: N
authors.lastname: Harel
authors.forename: Paul M
authors.initials: PM
authors.lastname: Thompson
authors.forename: Guillermo
authors.initials: G
authors.lastname: Sapiro
mesh_terms: D000465:Algorithms; D000818:Animals; D001921:Brain / Q000033:anatomy & histology*; D003627:Data Interpretation, Statistical; D056324:Diffusion Tensor Imaging / Q000379:methods*; D000882:Haplorhini; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D009413:Nerve Fibers, Myelinated / Q000648:ultrastructure*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity